Deduces enhancers from assay for transposase accessible chromatin (ATAC-seq) profiles by extracting and integrating ATAC-seq related data features with sequence related features. PEAS consists of a machine-learning framework based on neural networks. It allows users to refine enhancer annotations at the individual level. This tool can be used for describing ATAC-seq peak and reading distribution characteristics.

Performs single-cell assay of transposase-accessible chromatin followed by sequencing (scATAC-seq) data investigation. Destin prioritizes chromatin accessible regions that are more informative to differentiate cell types. It utilizes weighted principal component analysis (PCA), with peak-specific weights calculated based on the distances to transcription start sites (TSSs) as well as the relative frequency of chromatin accessibility peaks based on a broad range of reference experiments.

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